Slide 1

Slide 1 text

GEOGRAPHY OF RESEARCH AND URBAN HIERARCHY

Slide 2

Slide 2 text

FORTHCOMING WORK Chapter "Geography of research and urban hierarchy", to be published in Centrality and hierarchy of networks and territories, coordinated by Julie Fen-Chong. © ISTE Editions 2022 Materials and data associated to the github repository https://github.com/Marion- Mai/geo_of_research_and_urban_hierarchy, DOI: 10.5281/zenodo.5973814 The “Geography and demography” field of the Encyclopedia of Science published by the scientific publisher ISTE-Wiley – Editor: Denise Pumain

Slide 3

Slide 3 text

KEY QUESTIONS What is the link between geography of research and urban hierarchy? • To what extent is the distribution of research activities dependent on urban hierarchy? • Is city size a major determinant of scientific growth? • Is there a relationship between the size of cities and the type of scientific activities that take place there?

Slide 4

Slide 4 text

MAPPING THE GEOGRAPHY OF RESEARCH • R&D employment • Publication data • Citation counts Locales with WoS publications between 2000 and 2013 (articles, reviews & letters) Crédit: L. Jégou et M. Maisonobe

Slide 5

Slide 5 text

SCALING LAWS • A method successfully imported from biology (West et al., 1997) in the 2000s • Relation between a spatial distribution and the population size of cities • Three regimes: sublinear, linear, superlinear

Slide 6

Slide 6 text

Finance, O., Swerts, E. (2020). Scaling Laws in Urban Geography. Linkages with Urban Theories, Challenges and Limitations. In Theories and Models of Urbanization: Geography, Economics and Computing Sciences, D. Pumain (Ed.). Springer International Publishing, Cham, 67–96. « More than a simple concentration index » (Finance & Swerts, 2020)

Slide 7

Slide 7 text

From Pumain et al., Cybergeo, 2006

Slide 8

Slide 8 text

No content

Slide 9

Slide 9 text

RELATION TO CITY SIZE Research is an innovative activity Innovative activities concentrates in large metropolitan areas because research productivity is higher in large metropolitan areas (Bettencourt et al., 2007) VS The largest cities became larger because these cities were successful in adopting many successive innovation (Evolutionary theory, Pumain et al., 2006)

Slide 10

Slide 10 text

RELATION TO CITY SIZE • Metropolitan advantage according to Bettencourt et al. 2007 • Innovation stage according to Pumain et al. 2006 From Pumain et al., Cybergeo, 2006

Slide 11

Slide 11 text

ISSUE WITH THE R&D EMPLOYMENT CATEGORY • Does not always include employees in Universities and Hospitals • In France, these employees are classified in « Education » and « Health » sectors • Using publication data can be a way to overcome this limitation • Using publication data also enables to test the relation between productivity per capita and population size of cities

Slide 12

Slide 12 text

From Nomaler, Frenken & Heimericks, Plos ONE, 2014 – US data What about productivity?

Slide 13

Slide 13 text

No content

Slide 14

Slide 14 text

Marion Maisonobe. Géographie des activités de recherche et hiérarchies urbaines. Centralités et hiérarchies des réseaux et des territoires. Forthcoming. ISTE Editions. Michel Grossetti, Marion Maisonobe, Laurent Jégou, Béatrice Milard, Guillaume Cabanac. Spatial organisation of French research from the scholarly publication standpoint (1999-2017): Long-standing dynamics and policy-induced disorder. EPJ Web of Conferences, 2020.

Slide 15

Slide 15 text

Proximity between the geography of universities and the geography of Research in France • «The distribution of researchers in higher education, because it is globally linked to that of students (correlation coefficient of 0.995!), is increasingly modelled on the upper level of the French urban structure. » (Brocard, 1991, p.73) ; • During the 1990s, «higher education facilities tended to become as widespread as the facilities in which compulsory education is completed » so that in the late 2000s, « all major complete higher education hubs are less than two hours' drive from other centres in their region or neighbouring regions» (Baron, 2010). Madeleine Brocard. La science et les régions : géoscopie de la France. In: RECLUS-La Documentation Française. 1991. ; Myriam Baron. Les transformations de la carte universitaire depuis les années 1960 : constats et enjeux. In: Le Mouvement Social, vol. 233, no. 4, 2010. pp. 93-105

Slide 16

Slide 16 text

No content

Slide 17

Slide 17 text

THE CRITICAL MASS EFFECT IN QUESTION • Following the reports of University Alliance (2009 & 2011), we found no evidence of a size effect regarding the spatial distribution of scientific activities between urban areas (Grossetti et al., 2015, Handbook of geographies of innovation) • The spatial distribution of academics explains the spatial distribution of scientific activity (volume of publications per urban area) : • In France with a very good R2 (95%) - Grossetti et al., 2020 • In the UK with a very good R2 (88%) - Maisonobe, forthcoming → Agglomeration perimeters shared in Maisonobe, Jégou & Eckert, 2018, Cybergeo

Slide 18

Slide 18 text

P. A. Balland, C. Jara- Figueroa, S. G. Petralia, et al. Complex economic activities concentrate in large cities. In: Nat Hum Behav, 4, 2020. pp. 248– 254 Does complexity concentrate in metropolitan areas?

Slide 19

Slide 19 text

No content

Slide 20

Slide 20 text

No content

Slide 21

Slide 21 text

No content

Slide 22

Slide 22 text

DISCUSSION • Influence of urban perimeters (Arcaute et al., 2015) • Regression method (OLS) (Leitão et al., 2016) + zero values (Finance & Cottineau, 2019) • Residuals (low R2) • Other determinants than the city size (spatial logics by institution) • Other ways of measuring a spatial concentration and its evolution • Promising method: a dominance tree approach to systems of cities (Louail & Barthelemy, 2022)

Slide 23

Slide 23 text

SPATIAL LOGICS BY INSTITUTION • Universities • Town & gown relationships • HER decentralization policies • Hospitals • Research centers • Sectoral choices (i.e. space science) • Observatories • Stations and instruments (fieldwork geography)

Slide 24

Slide 24 text

Marion Maisonobe & Bastien Bernela. Exploring the borders of a transregional knowledge network. The case of a French research federation in green chemistry. International Conference on Scientometrics and Informetrics (ISSI 2019), Sep 2019, Rome, Italy.

Slide 25

Slide 25 text

Évolution de la répartition des citations reçues par les publications parues entre 2000 et 2010. Measuring spatial concentration dynamics

Slide 26

Slide 26 text

CHANGE IN THE GLOBAL CONCENTRATION OF PRODUCTION BY CLASSES OF CITIES Most publishing cities 2000* 2003* 2007* 2010* 2013* Trend Top 10 17.1 15.8 14.7 14.0 14.1 Top 20 24.6 23.4 22.2 21.3 21.6 Top 30 30.2 29.0 27.5 26.6 27.1 Top 50 39.1 37.7 36.0 35.1 35.6 Top 100 52.8 51.3 49.8 48.7 49.2 Top 200 69.7 68.3 66.7 65.3 65.1 Top 500 89.6 88.4 86.7 85.0 84.4 Top 1000 96.7 96.3 95.5 94.6 94.2 Total 100 100 100 100 100 Share of the global total of publications (%) Source: Science Citation Index Expanded (articles, reviews and letters) *mobile average over three years

Slide 27

Slide 27 text

Maisonobe, Marion. «Regional Distribution of Research: The Spatial Polarization in Question». In Handbook Bibliometrics, par Rafael Ball, 377-96. De Gruyter Saur, 2020. https://doi.org/10.1515/97831106 46610-036

Slide 28

Slide 28 text

ELABORATING ON OKABE & SADAHIRO’S WORK A. Identify the local centers from the initial Voronoi tessellation B. Draw new Voronoi polygons by considering these local centers only C. Determine the local centers, etc. A. In the end we obtain a dominance tree representing the spatial hierarchy of the system. Each node is characterized by its height h in the tree Louail & Barthelemy, 2022

Slide 29

Slide 29 text

APPLICATION: FRENCH AND US SYSTEMS OF CITIES (1880-2010) INSEE population data of French municipalities (since 1876) Compilation of US cities populations between 1790 and 2010 (every 10 years) Data come primarily from the US Census Bureau https://github.com/cestastanford/historical-us-city-populations Both datasets are public and available for free Louail & Barthelemy, 2022

Slide 30

Slide 30 text

POLICY IMPLICATIONS • Policy makers firmly believe in agglomeration effects favouring the metropolitan areas: « As the share of highly educated people tends to be larger in bigger cities, the productivity effects of city size and human capitals can thus reinforce each other » OECD, The Metropolitan Century, 2015, https://doi.org/10.1787/9789264228733-en • Demonstrating the lack of critical mass effects has important consequences as it invalidates the benefit of concentration of research funds and excellence policies targeting the biggest cities

Slide 31

Slide 31 text

The World is spiky Florida, 2005 « The concentration of creative talents in a few hotspots able to connect to the global system of cities is intensifying from the 1990s » (Florida, 2005)

Slide 32

Slide 32 text

Maisonobe, M., Jégou, L., & Cabanac, G., Peripheral Forces, Nature Index 563, S18-S19 (2018) https://www.nature.com/articles/d41586-018-07210-6

Slide 33

Slide 33 text

The GeoScimo website in french and english GEOgraphie de la production SCIentifique MOndiale URL : https://www.irit.fr/netscity An online tool (beta version) to analyse and map contemporary scientific networks at the city level